Pandas玩转数据（十四) -- 分组和透视功能实战

最新推荐文章于 2025-03-09 16:32:32 发布

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最新推荐文章于 2025-03-09 16:32:32 发布 · 2.5k 阅读

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#pandas #透视表 #分组 #python数据分析

本文聚焦于Pandas库在数据分组和透视表操作上的应用，通过实例探讨如何利用Python进行高效的数据分析汇总学习。

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数据分析汇总学习

https://blog.youkuaiyun.com/weixin_39778570/article/details/81157884

import pandas as pd
import numpy as np
from pandas import Series, DataFrame

# 打开美国航空公司数据
f = open('usa_flights.csv')
df = pd.read_csv(f)

df.head()
Out[6]: 
       flight_date unique_carrier  flight_num origin dest  arr_delay  \
0  02/01/2015 0:00             AA           1    JFK  LAX      -19.0   
1  03/01/2015 0:00             AA           1    JFK  LAX      -39.0   
2  04/01/2015 0:00             AA           1    JFK  LAX      -12.0   
3  05/01/2015 0:00             AA           1    JFK  LAX       -8.0   
4  06/01/2015 0:00             AA           1    JFK  LAX       25.0   

   cancelled  distance  carrier_delay  weather_delay  late_aircraft_delay  \
0          0      2475            NaN            NaN                  NaN   
1          0      2475            NaN            NaN                  NaN   
2          0      2475            NaN            NaN                  NaN   
3          0      2475            NaN            NaN                  NaN   
4          0      2475            0.0            0.0                  0.0   

   nas_delay  security_delay  actual_elapsed_time  
0        NaN             NaN                381.0  
1        NaN             NaN                358.0  
2        NaN             NaN                385.0  
3        NaN             NaN                389.0  
4       25.0             0.0                424.0  


# 对延误时间进行排序
df.sort_values('arr_delay', ascending=False).head()
Out[7]: 
           flight_date unique_carr